Daniel Kifer

Professor of Computer Science & Engineering

Daniel Kifer

Publication Tags

Learning Convolutional Neural Networks Neural Networks Soil Moisture Semantics Travel Time Simulation Neurons Hydrology Big Data Moisture Trajectories Time Series Deep Learning Pixels Flow Opinion Prolongation Coding Prediction Image Compression Physics Effect Baseline Landslide

Most Recent Publications

The neural coding framework for learning generative models

Alexander Ororbia, Daniel Kifer, 2022, Nature Communications

The Data Synergy Effects of Time-Series Deep Learning Models in Hydrology

Kuai Fang, Daniel Kifer, Kathryn Lawson, Dapeng Feng, Chaopeng Shen, 2022, Water Resources Research

Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder

Ankur Mali, Alexander G. Ororbia, Daniel Kifer, C. Lee Giles, 2022, on p. 471

Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms

Zeyu Ding, Yuxin Wang, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer, 2022, VLDB Journal

Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates

Savinay Nagendra, Daniel Kifer, Benjamin Mirus, Te Pei, Kathryn Lawson, Srikanth Banagere Manjunatha, Weixin Li, Hien Nguyen, Tong Qiu, Sarah Tran, Chaopeng Shen, 2022, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing on p. 4349-4370

DPGen: Automated Program Synthesis for Differential Privacy

Yuxin Wang, Zeyu DIng, Yingtai Xiao, Daniel Kifer, Danfeng Zhang, 2021, on p. 393-411

Physics-informed deep learning for prediction of CO<sub>2</sub> storage site response

Parisa Shokouhi, Vikas Kumar, Sumedha Prathipati, Seyyed A. Hosseini, Clyde Lee Giles, Daniel Kifer, 2021, Journal of Contaminant Hydrology

Omnilayout: Room layout reconstruction from indoor spherical panoramas

Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Mali, 2021, on p. 3701-3710

An Empirical Analysis of Recurrent Learning Algorithms in Neural Lossy Image Compression Systems

Ankur Mali, Alexander G. Ororbia, Dan Kifer, C. Lee Giles, 2021, 2021 Data Compression Conference (DCC) on p. 356

Optimizing fitness-for-use of differentially private linear Queries

Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer, 2021, Proceedings of the VLDB Endowment on p. 1730-1742

Most-Cited Papers

Pufferfish: A framework for mathematical privacy definitions

Daniel Kifer, Ashwin Machanavajjhala, 2014, ACM Transactions on Database Systems

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi John Chang, Sangram Ganguly, Kuo Lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li, Wen Ping Tsai, 2018, Hydrology and Earth System Sciences on p. 5639-5656

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

Kuai Fang, Chaopeng Shen, Daniel Kifer, Xiao Yang, 2017, Geophysical Research Letters on p. 11,030-11,039

Learning to extract semantic structure from documents using multimodal fully convolutional neural networks

Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, C. Lee Giles, 2017, on p. 4342-4351

Learning to read irregular text with attention mechanisms

Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles, 2017, on p. 3280-3286

Crime rate inference with big data

Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li, 2016, on p. 635-644

Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection

Dafang He, Scott Cohen, Brian Price, Daniel Kifer, C. Lee Giles, 2017, on p. 254-261

A Simple Baseline for Travel Time Estimation using Large-scale Trip Data

Hongjian Wang, Xianfeng Tang, Yu Hsuan Kuo, Daniel Kifer, Zhenhui Li, 2019, ACM Transactions on Intelligent Systems and Technology

Multi-scale FCN with cascaded instance aware segmentation for arbitrary oriented word spotting in the wild

Dafang He, Xiao Yang, Chen Liang, Zihan Zhou, Alex G. Ororbia, Daniel Kifer, C. Lee Giles, 2017, on p. 474-483

A neural temporal model for human motion prediction

Anand Gopalakrishnan, Ankur Mali, Dan Kifer, Lee Giles, Alexander G. Ororbia, 2019, on p. 12108-12117